The growth of Datacenter infrastructure is trending out of bounds, along with the pace in user activity and data generation in this digital era. However, the nature of the typical application deployment within the data center is changing to accommodate new business needs. Those changes introduce complexities in application deployment architecture and design, which cascade into requirements for a new generation of database technology (NoSQL) destined to ease that complexity. This webcast will discuss the modern data centers data centric application, the complexities that must be dealt with and common architectures found to describe and prescribe new data center aware services. Well look at the practical issues in implementation and overview current state of art in NoSQL database technology solving the problems of data center awareness in application development.

1. Data Centers and NoSQL Database
Robert Greene – Product Management

2.  Data Center Trends and Business Drivers
 Key Tech Requirements
 The Data Center Aware Application
 3 NoSQL Data Center Architectures
 Data Locality and Reliability Isolation
 Data Consistency Considerations
 NoSQL Data Center Implementation
 Summary - NoSQL & Data Centers
NoSQL - Enabling Data Center Applications

3. Data Centers - Trends and Drivers
 Trends – More deployments
• SMB’s going global
• Consumer facing
• Terabytes of Data
• Proximity and Rev
• Requirements
• Security
• Regulatory
• Availability
 IDC survey revenue>$1B or employees>5000
• 26% have 6 or more DC’s

4.  Cloud deployments
• SMB’s going global
• Consumer facing
• Terabytes of Data
• Proximity and Rev
• Requirements
• Security
• Regulatory
• Availability
Data Centers - Trends and Drivers

5.  Business Drivers
• Cost Optimization
• SaaS and Desktop Virtualization
• Globalized Sensor Data and M2M
• Big Data – Physics of IT
• Revenue
• Latency and Availability
Data Centers - Trends and Drivers

6.  Latency reduction
• Amazon study
• 100ms = 1% Revenue
• 150M dollars
• SMB seeing more data
• Physics
• More data = more time,
• Longer distance = more time
Key Technical Requirements

7.  Availability
• 2003 New York Blackout
• Dec 2012 AWS Outage
• Regulatory Mandates
Key Technical Requirements

8.  Process & Data Redundancy
• Specialized Needs
• Provisioning
• Placement
• Communications
• Encryption
• Security
• Data Availability
• Upgrade processing
• Failover processes
The Data Center Aware Application

9.  3 Prevalent Architectures
• Container
• Component
• Tag
NoSQL Data Center Architectures
Data
Replica
Replica
Data Center 1
Data Center 2
Data Center 3

10. NoSQL Data Center Deployment Architectures
Node
Data Replica Replica
Data Replica Replica
Hardware
Unit of Replication
Process
Container Based
 Strengths
• Allows Local Writes
• Simple Replication Admin
• Good Global Availability
 Weakness
• Many Data Copies
• High Bandwidth Rep
• No Consistent Reads
Durability & ConsistencyDurability & Consistency
Replication
More
Sites

11. NoSQL Data Center Deployment Architectures
Data Replica Replica
Hardware
Unit of Replication
Process
Component Based
 Strengths
• Minimal Data Copies
• Low Bandwidth Rep
• Good Regional Availability
• Simple Admin
 Weakness
• Network Latency
Sensitive
• Data placement
Durability & ConsistencySync Channel

12.  Strengths
• Complete Control
• Targeted Data
NoSQL Data Center Deployment Architectures
Node
Data Replica Replica Data Replica Replica
Hardware
Unit of Replication
Process
Data Replica Replica
TAG_A TAG_ATAG_A
Tag Based
 Weakness
• Coding Specific
• Brittle to system change
• Complex management
• Non-optimal data copies
Durability & Consistency Durability & Consistency
Sync Channel

13.  Hybrid Architectures
• Component (local reliability)
• Container (multi channel)
 Cloud Architectures
• Model Physical Infrastructure
• Geographic Regions
• Zoned local isolation points
• Power & Network only
NoSQL Data Center Architectures

14.  Physical - Points of Failure Isolation
• Disk, Server, Rack, Power, Network Switches
 Latency Placement Considerations
Data Locality and Reliability Isolation
Region
Data Center
Zone 3Zone 2Zone 1
RD R DR R A
Net Switches
Servers
Disks
High/Low Latency
Racks
Net Switches Net Switches
Low Latency
Power

15.  Multiple locations need to be kept in sync
 Latency – Read Consistency across Data Centers
• Consistency based on eventually consistent processes
• How to ensure you have the latest data if needed
• How to read locally to keep latency low
 Throughput – Write Durability across Data Centers
• Durability based on write copies, eventually everywhere
• How to get copies written without high latency
• How to resolve conflicting updates
 Techniques: quorum voting, vector clocks, timestamp
Data Consistency Considerations

16.  Container Architecture
• Reads and writes always local to the container
• No option to ensure consistent data
• Sync involves key differentiation scheme ( e.g. Merkle tree)
 Component Architecture
• Reads and writes optionally to local component
• Can request consistent operation ( possible latency cost )
• Sync involves log ordered sequencing ( no differentiation )
 Tagged Architecture
• Reads and writes explicit at the data level
• Can request consistent operation ( possible latency cost )
• Sync is application code dependent
Data Consistency Considerations

17.  Review of a few well known vendors
• Cassandra
• Hbase
• MongoDB
• OnDB
• Riak
NoSQL Data Center Implementation

18. Cassandra Data Center Implementation
 Data Center Architecture: Container
 Replication Unit: Node
 Reliability: Cluster
 Data Copies: RF * Data Center
 Durability: One, Local_Quorum
 Consistency: Timestamp
 Placement: Multiple copies per Data Center

19. Hbase Data Center Implementation
 Data Center Architecture: Tag
 Replication Unit: Column Family
 Reliability: Cluster
 Data Copies: RF x Clusters (family subset)
 Durability: ACID
 Consistency: Absolute
 Placement: None
 Extensions:
• Multi-Channel
Replication ( per
region server )

20. MongoDB Data Center Implementation
 Data Center Architecture: Tag
 Replication Unit: Range of Collection
 Reliability: Replica Set
 Data Copies: RF x Tagged Replica Set (range subset)
 Durability: WriteConcern
 Consistency: ReadConcern
 Placement: Hard Coded
 Extensions:
• Read-Only Shards

21. Riak Data Center Implementation
 Data Center Architecture: Container
 Replication Unit: Cluster
 Reliability: Local Cluster
 Data Copies: RF x Clusters
 Durability: One, Quorum, All
 Consistency: Vector Clock
 Placement: Multiple copies per cluster
 Extensions:
• Multi-Channel Sink
• Read-Only Cluster

22.  Data Center Architecture: Component
 Replication Unit: Zone
 Reliability: Zone(s)
 Data Copies: RF
 Durability: ACID, One, Quorum, All
 Consistency: Absolute, Quorum
 Placement: Copy per Zone
 Extensions:
• Local Quorum
• Read-Only Zones
OnDB – Oracle NoSQL DB Data Center
Data Replica Replica
Zone
Near Data Centers
Client ReadClient Write
Availability Group

23.  Data Center Deployments
• Increasingly Common: Cost, Revenue & Reliability Advantages
 The Data Center Aware Application ( latency & consistency )
Summary – NoSQL & Data Centers
Component X
Container X X
Tag X X
Near Data Centers X X X
Multi Channel
X
Disaster Recovery
Placement
Far Data Centers Placement X X Placement
Consistent Data X X
In-Consistent Data X X X
Data Size - Copies Low High High Low Medium

24. Oracle NoSQL DB Resources
• NoSQL Database Downloads
http://www.oracle.com/technetwork/products/nosqldb/downloads/index.html
• NoSQL Database Documentation
http://www.oracle.com/technetwork/products/nosqldb/documentation/index.html
• NoSQL Database Contacts
• David Segleau – Director Product Management dave.segleau@oracle.com
• Robert Greene – Senior Principle Product Manager robert.c.greene@oracle.com